{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true,
    "ExecuteTime": {
     "end_time": "2024-07-15T08:48:22.104570100Z",
     "start_time": "2024-07-15T08:48:21.817498700Z"
    }
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "outputs": [
    {
     "data": {
      "text/plain": "a    0\nc    1\ne    2\nf    3\ng    4\ndtype: int64"
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Series\n",
    "s1 = pd.Series(np.arange(4), index=['a', 'b', 'c', 'd'])\n",
    "s2 = pd.Series(np.arange(5), index=['a', 'c', 'e', 'f', 'g'])"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-07-15T08:50:24.863459Z",
     "start_time": "2024-07-15T08:50:24.859089600Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "outputs": [
    {
     "data": {
      "text/plain": "a    0.0\nb    NaN\nc    3.0\nd    NaN\ne    NaN\nf    NaN\ng    NaN\ndtype: float64"
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s1 + s2"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-07-15T08:51:00.921290100Z",
     "start_time": "2024-07-15T08:51:00.917919700Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "outputs": [],
   "source": [
    "# dataframe\n",
    "df1 = pd.DataFrame(np.arange(12).reshape(4, 3),\n",
    "                   index=['a', 'b', 'c', 'd'],\n",
    "                   columns=list('ABC'))\n",
    "df2 = pd.DataFrame(np.arange(9).reshape(3, 3),\n",
    "                   index=['a', 'd', 'f'],\n",
    "                   columns=list('ABD'))"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-07-15T08:57:43.133029700Z",
     "start_time": "2024-07-15T08:57:43.127458600Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "outputs": [
    {
     "data": {
      "text/plain": "   A   B   C\na  0   1   2\nb  3   4   5\nc  6   7   8\nd  9  10  11",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>A</th>\n      <th>B</th>\n      <th>C</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>a</th>\n      <td>0</td>\n      <td>1</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>b</th>\n      <td>3</td>\n      <td>4</td>\n      <td>5</td>\n    </tr>\n    <tr>\n      <th>c</th>\n      <td>6</td>\n      <td>7</td>\n      <td>8</td>\n    </tr>\n    <tr>\n      <th>d</th>\n      <td>9</td>\n      <td>10</td>\n      <td>11</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-07-15T08:57:46.166505700Z",
     "start_time": "2024-07-15T08:57:46.163093900Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "outputs": [
    {
     "data": {
      "text/plain": "   A  B  D\na  0  1  2\nd  3  4  5\nf  6  7  8",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>A</th>\n      <th>B</th>\n      <th>D</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>a</th>\n      <td>0</td>\n      <td>1</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>d</th>\n      <td>3</td>\n      <td>4</td>\n      <td>5</td>\n    </tr>\n    <tr>\n      <th>f</th>\n      <td>6</td>\n      <td>7</td>\n      <td>8</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-07-15T08:58:13.946487Z",
     "start_time": "2024-07-15T08:58:13.919403600Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "outputs": [
    {
     "data": {
      "text/plain": "      A     B   C   D\na   0.0   2.0 NaN NaN\nb   NaN   NaN NaN NaN\nc   NaN   NaN NaN NaN\nd  12.0  14.0 NaN NaN\nf   NaN   NaN NaN NaN",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>A</th>\n      <th>B</th>\n      <th>C</th>\n      <th>D</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>a</th>\n      <td>0.0</td>\n      <td>2.0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>b</th>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>c</th>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>d</th>\n      <td>12.0</td>\n      <td>14.0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>f</th>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1 + df2"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-07-15T08:58:34.396757500Z",
     "start_time": "2024-07-15T08:58:34.393240200Z"
    }
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "2.使用填充值的算术方法"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "outputs": [
    {
     "data": {
      "text/plain": "a    0.0\nb    1.0\nc    3.0\nd    3.0\ne    2.0\nf    3.0\ng    4.0\ndtype: float64"
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s1.add(s2, fill_value=0)"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-07-15T09:28:47.068569Z",
     "start_time": "2024-07-15T09:28:47.065016500Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "outputs": [
    {
     "data": {
      "text/plain": "      A     B     C    D\na   0.0   2.0   2.0  2.0\nb   3.0   4.0   5.0  NaN\nc   6.0   7.0   8.0  NaN\nd  12.0  14.0  11.0  5.0\nf   6.0   7.0   NaN  8.0",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>A</th>\n      <th>B</th>\n      <th>C</th>\n      <th>D</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>a</th>\n      <td>0.0</td>\n      <td>2.0</td>\n      <td>2.0</td>\n      <td>2.0</td>\n    </tr>\n    <tr>\n      <th>b</th>\n      <td>3.0</td>\n      <td>4.0</td>\n      <td>5.0</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>c</th>\n      <td>6.0</td>\n      <td>7.0</td>\n      <td>8.0</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>d</th>\n      <td>12.0</td>\n      <td>14.0</td>\n      <td>11.0</td>\n      <td>5.0</td>\n    </tr>\n    <tr>\n      <th>f</th>\n      <td>6.0</td>\n      <td>7.0</td>\n      <td>NaN</td>\n      <td>8.0</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.add(df2, fill_value=0)"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-07-15T09:33:10.690077500Z",
     "start_time": "2024-07-15T09:33:10.682688200Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "outputs": [
    {
     "data": {
      "text/plain": "          A         B         C\na       inf  1.000000  0.500000\nb  0.333333  0.250000  0.200000\nc  0.166667  0.142857  0.125000\nd  0.111111  0.100000  0.090909",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>A</th>\n      <th>B</th>\n      <th>C</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>a</th>\n      <td>inf</td>\n      <td>1.000000</td>\n      <td>0.500000</td>\n    </tr>\n    <tr>\n      <th>b</th>\n      <td>0.333333</td>\n      <td>0.250000</td>\n      <td>0.200000</td>\n    </tr>\n    <tr>\n      <th>c</th>\n      <td>0.166667</td>\n      <td>0.142857</td>\n      <td>0.125000</td>\n    </tr>\n    <tr>\n      <th>d</th>\n      <td>0.111111</td>\n      <td>0.100000</td>\n      <td>0.090909</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "1 / df1"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-07-15T09:40:24.994604900Z",
     "start_time": "2024-07-15T09:40:24.989128400Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "outputs": [
    {
     "data": {
      "text/plain": "          A         B         C\na       inf  1.000000  0.500000\nb  0.333333  0.250000  0.200000\nc  0.166667  0.142857  0.125000\nd  0.111111  0.100000  0.090909",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>A</th>\n      <th>B</th>\n      <th>C</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>a</th>\n      <td>inf</td>\n      <td>1.000000</td>\n      <td>0.500000</td>\n    </tr>\n    <tr>\n      <th>b</th>\n      <td>0.333333</td>\n      <td>0.250000</td>\n      <td>0.200000</td>\n    </tr>\n    <tr>\n      <th>c</th>\n      <td>0.166667</td>\n      <td>0.142857</td>\n      <td>0.125000</td>\n    </tr>\n    <tr>\n      <th>d</th>\n      <td>0.111111</td>\n      <td>0.100000</td>\n      <td>0.090909</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.rdiv(1)  # 字母r表示反转参数"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-07-15T09:40:57.914205700Z",
     "start_time": "2024-07-15T09:40:57.909690300Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "outputs": [
    {
     "data": {
      "text/plain": "   A   B  D\na  0   1  0\nb  3   4  0\nc  6   7  0\nd  9  10  0",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>A</th>\n      <th>B</th>\n      <th>D</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>a</th>\n      <td>0</td>\n      <td>1</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>b</th>\n      <td>3</td>\n      <td>4</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>c</th>\n      <td>6</td>\n      <td>7</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>d</th>\n      <td>9</td>\n      <td>10</td>\n      <td>0</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.reindex(columns=df2.columns, fill_value=0)"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-07-15T09:42:42.321880500Z",
     "start_time": "2024-07-15T09:42:42.313995100Z"
    }
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "3.DataFrame和Series混合运算"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "outputs": [
    {
     "data": {
      "text/plain": "array([[ 0,  1,  2,  3],\n       [ 4,  5,  6,  7],\n       [ 8,  9, 10, 11]])"
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "arr = np.arange(12).reshape(3,4)\n",
    "arr"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-07-15T12:17:33.249569800Z",
     "start_time": "2024-07-15T12:17:33.240957Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0 1 2 3]\n"
     ]
    }
   ],
   "source": [
    "print(arr[0])"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-07-15T12:18:07.578141300Z",
     "start_time": "2024-07-15T12:18:07.571632100Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "outputs": [
    {
     "data": {
      "text/plain": "array([[0, 0, 0, 0],\n       [4, 4, 4, 4],\n       [8, 8, 8, 8]])"
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "arr-arr[0]"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-07-15T12:18:47.192224Z",
     "start_time": "2024-07-15T12:18:47.185710500Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "outputs": [
    {
     "data": {
      "text/plain": "   A   B   C\na  0   1   2\nb  3   4   5\nc  6   7   8\nd  9  10  11",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>A</th>\n      <th>B</th>\n      <th>C</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>a</th>\n      <td>0</td>\n      <td>1</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>b</th>\n      <td>3</td>\n      <td>4</td>\n      <td>5</td>\n    </tr>\n    <tr>\n      <th>c</th>\n      <td>6</td>\n      <td>7</td>\n      <td>8</td>\n    </tr>\n    <tr>\n      <th>d</th>\n      <td>9</td>\n      <td>10</td>\n      <td>11</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-07-15T12:18:59.073448800Z",
     "start_time": "2024-07-15T12:18:59.048585100Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "outputs": [
    {
     "data": {
      "text/plain": "A    0\nB    1\nC    2\nName: a, dtype: int64"
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s3=df1.iloc[0]\n",
    "s3"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-07-15T12:19:22.981518100Z",
     "start_time": "2024-07-15T12:19:22.932015500Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "outputs": [
    {
     "data": {
      "text/plain": "   A  B  C\na  0  0  0\nb  3  3  3\nc  6  6  6\nd  9  9  9",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>A</th>\n      <th>B</th>\n      <th>C</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>a</th>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>b</th>\n      <td>3</td>\n      <td>3</td>\n      <td>3</td>\n    </tr>\n    <tr>\n      <th>c</th>\n      <td>6</td>\n      <td>6</td>\n      <td>6</td>\n    </tr>\n    <tr>\n      <th>d</th>\n      <td>9</td>\n      <td>9</td>\n      <td>9</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1-s3"
   ],
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     "end_time": "2024-07-15T12:19:47.091775800Z",
     "start_time": "2024-07-15T12:19:47.087254500Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "outputs": [
    {
     "data": {
      "text/plain": "a    0\nb    3\nc    6\nd    9\nName: A, dtype: int64"
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s4=df1['A']\n",
    "s4"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-07-15T12:20:43.436889800Z",
     "start_time": "2024-07-15T12:20:43.427641400Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "outputs": [
    {
     "data": {
      "text/plain": "   A  B  C\na  0  1  2\nb  0  1  2\nc  0  1  2\nd  0  1  2",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>A</th>\n      <th>B</th>\n      <th>C</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>a</th>\n      <td>0</td>\n      <td>1</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>b</th>\n      <td>0</td>\n      <td>1</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>c</th>\n      <td>0</td>\n      <td>1</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>d</th>\n      <td>0</td>\n      <td>1</td>\n      <td>2</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.sub(s4,axis='index')"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-07-15T12:22:42.184058900Z",
     "start_time": "2024-07-15T12:22:42.177311100Z"
    }
   }
  }
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